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Share of women with no formal education

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Global Education

About this data

Source
Barro and Lee (2015); Lee and Lee (2016) – with major processing by Our World in Data
Last updated
July 17, 2023
Date range
1870–2040
Unit
%

Sources and processing

This data is based on the following sources

Using the estimates on school enrollment and population structure, Barro and Lee have constructed projections of educational attainment for the population, disaggregated by gender and age group (15–24, 25–64, and 15–64) for 146 countries from 2015 to 2040 at five-year intervals.

They first use the 2010 data on educational attainment by age group as benchmark figures to project the educational attainment of the population by age group for the next three decades. They then estimate the distribution of educational attainment for the younger population, aged 15-24, at the five-year intervals from 2015 to 2040 and then forward-extrapolate the estimates to construct the distribution of educational attainment for the older population groups. For the population structure, they use existing U.N. projections. For the detailed explanation of the estimation method, see Barro and Lee (2015, chapter 3).

Retrieved on
November 20, 2023
Retrieved from
http://www.barrolee.com/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Barro, Robert J. and Jong-Wha Lee, Education Matters: Global Schooling Gains from the 19th to the 21st Century (Oxford University Press, 2015)

Datasets on estimated school enrollment ratios from 1820 to 2010 and estimated educational attainment for the total, female, and male populations from 1870 to 2010. The estimates are available in five-year intervals for 111 countries.

Datasets were last updated in 2021 September. The research provides insightful analysis on the progression and trends of educational attainment over a long historical period, offering a comprehensive understanding of educational developments globally.

Retrieved on
November 20, 2023
Retrieved from
https://barrolee.github.io/BarroLeeDataSet/DataLeeLee.html
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Lee, Jong-Wha and Hanol Lee, 2016, “Human Capital in the Long Run,” Journal of Development Economics, vol. 122, pp. 147-169.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

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Notes on our processing step for this indicator

Historical data up to the year 2010 has been sourced from 'Human Capital in the Long Run' by Lee and Lee (2016). This historical data was then combined with recent projections provided by Barro ane Lee (2015).

Regional aggregates were computed by Our World in Data through yearly population-weighted averages, where annual values are proportionally adjusted to emphasize the influence of larger populations.

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Share of women with no formal education”, part of the following publication: Hannah Ritchie, Veronika Samborska, Natasha Ahuja, Esteban Ortiz-Ospina and Max Roser (2023) - “Global Education”. Data adapted from Barro and Lee, Lee and Lee. Retrieved from https://ourworldindata.org/grapher/share-of-women-15-years-and-older-with-no-education [online resource]
How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Barro and Lee (2015); Lee and Lee (2016) – with major processing by Our World in Data

Full citation

Barro and Lee (2015); Lee and Lee (2016) – with major processing by Our World in Data. “Share of women with no formal education” [dataset]. Barro and Lee, “Projections of Educational Attainment”; Lee and Lee, “Human Capital in the Long Run” [original data]. Retrieved November 1, 2024 from https://ourworldindata.org/grapher/share-of-women-15-years-and-older-with-no-education